Collaborative Research: Investigating Supercell/Tornado Genesis, Structure and Evolution Using Observations and Numerical Models

合作研究：利用观测和数值模型研究超级细胞/龙卷风的起源、结构和演化

• 批准号: 0843269
• 负责人: Matthew Gilmore
• 金额: $ 39万
• 依托单位: University of North Dakota Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0843269&HistoricalAwards=false
• 关键词: Collaborative; Research; Investigating; Supercell; Tornado

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).The goal of this research is to improve understanding of severe convective storms using numerical models with particular attention to genesis, structure and evolution of supercells and tornadoes in increasingly realistic environmental conditions. Research questions include: 1) Why some supercell-spawned tornadoes are particularly long-lived? 2) How environmental conditions influence tornado genesis, intensity, and longevity? 3) How capping inversions and microphysical makeup influence cold pool strength and the development of low-level rotation in supercell storms?4) How storm interaction and mergers impact tornado genesis?Observations, numerical modeling and data analysis will be used to address the research questions. The methodological approaches build on the Principal Investigators' (PIs) past work including the successful simulation of an intense and long-lived supercell-spawned tornado, simulations of supercell storm environment at 1 km resolution, assimilation of polarimetric radar observations, and coarse-resolution simulations of storm interactions. Observations will be used to guide parameter studies and for data assimilation while modeling will provide consistent and high resolution space and time data sets for analysis and the means to explore controlled parameter spaces. The modeling studies build on advances in model physics, model parallelization/nesting, new methods for initiating sustained storms in the presence of capping inversions, and ensemble Kalman filter based data assimilation methods. The research will take advantage of the availability of computing systems approaching the petascale as well as future systems such as Blue Waters to be deployed at the University of Illinois in 2011 which will be capable of sustaining petaflop performance for weather and storm simulation. Intellectual Merit of Proposal: The work is aimed at increasing the understanding of supercell/tornado genesis, and structure and evolution. Numerical simulation provides a unique approach for testing hypotheses as well as providing complete data sets for analysis and visualization. It also provides a means to simulate multiple scales, namely the supercell and any tornadoes embedded within it. Of particular interest is determining what environmental conditions and what balance of forces are required for simulations of quasi-steady and long-lived supercell-spawned tornadoes. Broader Impacts: The research will potentially improve public warnings. In particular, the PIs will contribute to understanding why some supercell storms produce tornadoes while others do not. Given the upgrade of the WSR-88D radar network that is currently underway, research on the assimilation of polarimetric radar data will provide new insight as to how to best use this data in storm forecasting. Research findings will be communicated via conference presentations, peer-reviewed journal articles and instructional modules for wider use by meteorological education, research and operational communities. The results will be used in classes at the University of Illinois and University of North Dakota. In addition, the researchers will be working with National Center for Supercomputer Applications on a storm exhibit at the Chicago Museum of Science and Industry. The latter will include interactive tools for exploring simulation data as well as visualizations from supercell/tornado simulations. Three graduate students will be supported and cross institution collaboration will be fostered by the work between two academic institutions.

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。本研究的目的是利用数值模型提高对强对流风暴的认识，特别关注超级单体和龙卷风在日益现实的环境条件下的发生、结构和演变。研究问题包括：1)为什么一些超级细胞产生的龙卷风寿命特别长？2)环境条件如何影响龙卷风的发生、强度和寿命？3)封顶逆温和微物理组成如何影响超级单体风暴中冷池强度和低层旋转的发展？4)风暴相互作用和合并如何影响龙卷风的形成？观察，数值模拟和数据分析将用于解决研究问题。方法方法建立在首席研究员（pi）过去的工作基础上，包括成功模拟强烈和长寿命的超级细胞产生的龙卷风，模拟1公里分辨率的超级细胞风暴环境，同化极化雷达观测，以及风暴相互作用的粗分辨率模拟。观测将用于指导参数研究和数据同化，而建模将提供一致和高分辨率的空间和时间数据集，用于分析和探索受控参数空间的手段。建模研究建立在模型物理学、模型并行化/嵌套、在覆盖反转中启动持续风暴的新方法和基于集合卡尔曼滤波的数据同化方法的基础上。这项研究将利用现有的千万亿次计算系统以及未来的系统，如2011年伊利诺伊大学将部署的Blue Waters，该系统将能够在天气和风暴模拟中保持千万亿次的性能。提案的智力价值：这项工作旨在增加对超级单体/龙卷风成因、结构和进化的理解。数值模拟为测试假设以及为分析和可视化提供完整的数据集提供了一种独特的方法。它还提供了一种方法来模拟多个尺度，即超级单体和任何嵌入其中的龙卷风。特别令人感兴趣的是确定什么样的环境条件和什么样的力量平衡是模拟准稳定和长寿命的超级细胞产生的龙卷风所需要的。更广泛的影响：这项研究可能会改善公共警告。特别是，pi将有助于理解为什么一些超级单体风暴产生龙卷风，而另一些则不会。鉴于目前正在进行的WSR-88D雷达网络的升级，极化雷达数据同化的研究将为如何最好地利用这些数据进行风暴预报提供新的见解。研究成果将通过会议报告、同行评议的期刊文章和教学模块进行交流，供气象教育、研究和业务界更广泛地使用。研究结果将用于伊利诺伊大学和北达科他大学的课堂。此外，研究人员将与国家超级计算机应用中心合作，在芝加哥科学与工业博物馆举办风暴展览。后者将包括用于探索模拟数据的交互式工具以及超级细胞/龙卷风模拟的可视化。三名研究生将获得资助，两所学术机构之间的合作将促进跨机构合作。